This paper proposes a set of Level 3 Basic Linear Algebra Subprograms and associated kernels for sparse matrices. We discuss the design, implementation and use of subprograms for the multiplication of a full matrix by a sparse one and for the solution of sparse triangular systems with one or more (full) right-hand sides. We include routines for checking the input data, generating a new sparse data structure from that input, and scaling a sparse matrix. The new data structure for the transformation can be specified by the user or can be chosen automatically by vendors to be efficient on their machines. We also include routines for permuting the columns of a sparse matrix and one for permuting the rows of a full matrix. A major aim is ...
This chapter provides routines for the iterative solution of large sparse nonsymmetric and symmetri
This report describes a subprogram, SPLP(), for solving linear programming problems. The package of ...
SparseM provides some basic R functionality for linear algebra with sparse matrices. Use of the pack...
Abstract. Numerical linear algebra and combinatorial optimization are vast subjects; as is their int...
We discuss the interface design for the Sparse Basic Linear Algebra Subprograms (BLAS), the kernels ...
This book is primarily intended as a research monograph that could also be used in graduate courses ...
This paper describes two portable packages for general-purpose sparse matrix computations: SPARSKIT...
Abstract. Sparse matrix-matrix multiplication (or SpGEMM) is a key primitive for many high-performan...
42 pages, available as LIP research report RR-2009-15Numerical linear algebra and combinatorial opti...
Many computationally intensive problems in engineering and science give rise to the solution of larg...
Abstract. On many high-speed computers the dense matrix technique is preferable to sparse matrix tec...
Matrix computations lie at the heart of most scientific computational tasks. The solution of linear ...
Abstract. Variants of the p4 algorithm of Hellerman and Rarick and the p5 algorithm of Erisman, Grim...
AbstractThe matrix-vector multiplication operation is the kernel of most numerical algorithms.Typica...
Abstract. Sparse matrix-vector multiplication is an important computational kernel that tends to per...
This chapter provides routines for the iterative solution of large sparse nonsymmetric and symmetri
This report describes a subprogram, SPLP(), for solving linear programming problems. The package of ...
SparseM provides some basic R functionality for linear algebra with sparse matrices. Use of the pack...
Abstract. Numerical linear algebra and combinatorial optimization are vast subjects; as is their int...
We discuss the interface design for the Sparse Basic Linear Algebra Subprograms (BLAS), the kernels ...
This book is primarily intended as a research monograph that could also be used in graduate courses ...
This paper describes two portable packages for general-purpose sparse matrix computations: SPARSKIT...
Abstract. Sparse matrix-matrix multiplication (or SpGEMM) is a key primitive for many high-performan...
42 pages, available as LIP research report RR-2009-15Numerical linear algebra and combinatorial opti...
Many computationally intensive problems in engineering and science give rise to the solution of larg...
Abstract. On many high-speed computers the dense matrix technique is preferable to sparse matrix tec...
Matrix computations lie at the heart of most scientific computational tasks. The solution of linear ...
Abstract. Variants of the p4 algorithm of Hellerman and Rarick and the p5 algorithm of Erisman, Grim...
AbstractThe matrix-vector multiplication operation is the kernel of most numerical algorithms.Typica...
Abstract. Sparse matrix-vector multiplication is an important computational kernel that tends to per...
This chapter provides routines for the iterative solution of large sparse nonsymmetric and symmetri
This report describes a subprogram, SPLP(), for solving linear programming problems. The package of ...
SparseM provides some basic R functionality for linear algebra with sparse matrices. Use of the pack...